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基于雷达基数据的风暴单体跟踪与预报 被引量:1
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作者 路志英 赵冬阳 《传感器与微系统》 CSCD 2017年第7期16-18,22,共4页
多普勒雷达基数据对风暴单体的跟踪及预报具有十分重要的意义。针对雷达监测预报的原理和特点,建设性地提出了一种跟踪和预报方法。根据"体扫间隔,特征相似,近距离优先"三个匹配准则来匹配两时刻的风暴单体,再利用加权最小二... 多普勒雷达基数据对风暴单体的跟踪及预报具有十分重要的意义。针对雷达监测预报的原理和特点,建设性地提出了一种跟踪和预报方法。根据"体扫间隔,特征相似,近距离优先"三个匹配准则来匹配两时刻的风暴单体,再利用加权最小二乘法对风暴单体在下一时刻的位置进行预报。通过对天津市2005~2011年间74个天气过程的实验和评估,结果表明:该方法的可预报单体数更多,单体平均预报误差更小,能够更好地实现风暴单体的跟踪及预报。 展开更多
关键词 雷达基数据 风暴单体 跟踪和预报 平均预报误差
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基于动态主元分析法的传感器故障检测 被引量:8
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作者 李果 张鹏 +2 位作者 李学仁 魏瑞轩 冀捐灶 《数据采集与处理》 CSCD 北大核心 2008年第3期338-341,共4页
提出了一种基于动态主元分析的传感器故障检测方法。利用数据矩阵前t时刻和当前时刻的数据,建立多变量多时刻的自回归统计模型。计算主元数据矩阵,建立动态主元模型。以测量速度最慢的传感器的测量周期为统一采样周期,4个连续采样周期... 提出了一种基于动态主元分析的传感器故障检测方法。利用数据矩阵前t时刻和当前时刻的数据,建立多变量多时刻的自回归统计模型。计算主元数据矩阵,建立动态主元模型。以测量速度最慢的传感器的测量周期为统一采样周期,4个连续采样周期为一个诊断周期,建立动态三维测量矩阵,采用残差的平方预报误差的指数加权移动平均(Squared prediction error-Exponentially weighted moving average,SPE-EWMA)模型检测传感器故障。在只存在传感器故障的前提下,模拟发动机开车过程中几种典型的渐变性故障和突变性故障,实验结果表明,算法实时跟踪了各种检测指标的变化,准确检测出故障传感器。 展开更多
关键词 传感器 主元分析方法 平方预报误差指数加权移动平均(SPE—EWMA) 故障检测
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The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii
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作者 Jie FENG Jianping LI +2 位作者 Jing ZHANG Deqiang LIU Ruiqiang DING 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2019年第3期271-278,339,共9页
It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the rel... It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2^(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases. 展开更多
关键词 attractor radius ensemble forecasting ensemble mean forecast error saturation
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